Variations in Rates of Biological Production in the Beaufort Gyre as the Arctic Changes: Rates From 2011 to 2016
Bibliographic record
Abstract
Abstract The Arctic Ocean is experiencing profound environmental changes as the climate warms. Understanding how these changes will affect Arctic biological productivity is key for predicting future Arctic ecosystems and the global CO2balance. Here we use in situ gas measurements to quantify rates of gross oxygen production (GOP, total photosynthesis) and net community production (NCP, net CO2drawdown by the biological pump) in the mixed layer in summer or fall from 2011 to 2016 in the Beaufort Gyre. NCP and GOP show spatial and temporal variations with higher values linked with lower concentrations of sea ice and increased upper ocean stratification. Mean rates of GOP range from 8 ± 1 to 54 ± 9 mmol O2·m−2·d−1with the highest mean rates occurring in summer of 2012. Mean rates of NCP ranged from 1.3 ± 0.2 to 2.9 ± 0.5 mmol O2·m−2·d−1. The mean ratio of NCP/GOP, a measure of how efficiently the ecosystem is recycling its nutrients, ranged from 0.04 to 0.17, similar to ratios observed at lower latitudes. Additionally, a large increase in total photosynthesis that occurred in 2012, a year of historically low sea ice coverage, persisted for many years. Taken together, these data provide one of the most complete characterizations of interannual variations of biological productivity in this climatically important region, can serve as a baseline for future changes in rates of production, and give an intriguing glimpse of how this region of the Arctic may respond to future lack of sea ice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".